The chromatin landscape of healthy and injured cell types in the human kidney

Abstract

There is a need to define regions of gene activation or repression that control human kidney cells in states of health, injury, and repair to understand the molecular pathogenesis of kidney disease and design therapeutic strategies. Comprehensive integration of gene expression with epigenetic features that define regulatory elements remains a significant challenge. We measure dual single nucleus RNA expression and chromatin accessibility, DNA methylation, and H3K27ac, H3K4me1, H3K4me3, and H3K27me3 histone modifications to decipher the chromatin landscape and gene regulation of the kidney in reference and adaptive injury states. We establish a spatially-anchored epigenomic atlas to define the kidney’s active, silent, and regulatory accessible chromatin regions across the genome. Using this atlas, we note distinct control of adaptive injury in different epithelial cell types. A proximal tubule cell transcription factor network of ELF3, KLF6, and KLF10 regulates the transition between health and injury, while in thick ascending limb cells this transition is regulated by NR2F1. Further, combined perturbation of ELF3, KLF6, and KLF10 distinguishes two adaptive proximal tubular cell subtypes, one of which manifested a repair trajectory after knockout. This atlas will serve as a foundation to facilitate targeted cell-specific therapeutics by reprogramming gene regulatory networks.

Comprehensive analysis of the endothelin system in the kidneys of mice, rats, and humans

“…Unsupervised cluster lead to the identification and annotation of 57 clusters of all the expected cell types (e.g., epithelial, vascular, immune cells, Figure 1 A, Supplementary Table S3). The KPMP also annotated ‘adaptive’ clusters that represent adaptive/maladaptive/repairing cells, ‘cycling’ those that have increased cell cycle markers, ‘degenerative’ those that have lost differentiation markers, and ‘transitional’ those that have an intermediate genetic signature sharing the same parental lineage [ 35 ]. All cell type annotations and definitions can be found in Supplementary Table S3.…”

“…On June 1, 2022 all publicly available kidney single cell or single nucleus RNA-sequencing data from human, rat, and C57bl/6j mice were downloaded. Cell clustering of the human data obtained from the Kidney Precision Medicine Project (KPMP) data was used as provided [ 35 , 36 ]. The rat and mouse data were re-analyzed to generate de novo cluster maps, using the package Seurat version 4.1.1.…”